Upon initial consideration, new advances in automation and machine learning seem like one of the greatest threats to the modern labor market. Numerous predictions thus far have foreseen a future labor market in which humans are replaced by machines that can perform automated tasks without the financial burden of a wage. However, a recent study from the McKinsey Global Institute shows that simply replacing humans with machines will not lead to a significant growth in productivity. The only way that automation can improve productivity is if humans work alongside technology.
McKinsey researchers performed the study by focusing on how automation would affect types of tasks and activities performed on the job instead of specific occupations. As a result, they found that while predictable physical activities, which make up 51 percent of occupational activities, are the most vulnerable to being automated, only five percent of occupations would be replaced entirely by automation. This does not mean that automation will not take a large role in the future. In fact, 60 percent of occupations should expect 30 percent of their activities to be replaced by technology. According to the study, these changes would be for the better, leading to a productivity growth of between 0.8 and 1.4 percent annually if humans perform their tasks alongside automated processes. But it would be foolish to believe that replacing entire occupations will achieve the same results.
This is clear when one studies the nature of the activities that can and cannot be replaced by automation. According to another McKinsey Global Institute report, predictable and unpredictable physical work, as well as other structured tasks like data processing will easily be performed by machines in the near future, if they haven’t already. Management and development tasks are more difficult to program into computers because of the human nature of the work. There must always be humans in the workforce, even if only to man machines, and as long as this continues, there must be some form of management structure. When development is considered, automated training systems can accomplish much of the teaching that is necessary; however, as is the case with education now, there is a necessary human touch to both explaining and enforcing training to encourage development.
Similarly, the McKinsey study found that in some occupations, it is difficult to automate tasks that require a great deal of expertise. While some fields such as education can find great value in the expertise that technology can contribute to learning, other fields require skill that can only be brought about by experience, not by informational learning. Examples include jobs in retail and sales. Another prominent case would be that of the nursing field, as the study argues. While some of the physical tasks that a nurse performs could be automated, the practical experience and human interaction are still a necessary part of the job that cannot be replaced by a computer.
However, this is not to say that the labor force will not have to adapt to a new structure with the introduction of automation. In fact, it is likely that people will find themselves pushed out of structured, programmable jobs and into management, development, or creative jobs. This would maximize the potential for both human and machine to increase productivity.
Most of the arguments against automation thus far have been driven by a fear of simply eliminating entire jobs and leaving people unemployed. Now there is an economic incentive to preserve human employment instead of completely replacing jobs. It is clearly evident that the productivity can only grow if people use technology to increase efficiency and aid them with their jobs. Yes, the labor market will shift, and there will be a clearer distinction between jobs that can be automated and jobs that cannot, at least with the technology that is presently available. However, there is no justification for machines to replace humans across the board.
Alex Oliveira is a staff columnist for the Daily Campus. She can be reached via email at firstname.lastname@example.org.